Stability Analysis for Cohen-Grossberg NeuraL Networks with Inverse Lipschitz Neuron Activations and Impulses

摘要

Impulsive Cohen-Grossberg neural network (CGNN) with inverse Lipschitz neuron activations is studied in this paper. Some stability criteria are obtained to ensure the global exponential stability of the equilibrium point of the impulsive CGNN by topological degree theory, Lyapunov function method and linear matrix inequality. Finally, a numerical example shows the effectiveness of the theoretical result.